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Description

PaCeQuant, an ImageJ-based tool, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images, and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based and PC-specific object descriptors.
In addition, the developers included a method for classification and analysis of lobes at two-cell-junctions and three-cell-junctions, respectively. They provide an R script for graphical visualization and statistical analysis. They validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools, and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes.
PaCeQuant thus provides a platform for robust, efficient and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets.